Nonlinear modulation with low-power sensor networks using undersampling

Abstract

Nonlinear modulation is a promising technique for ultrasonic non-destructive damage identification. A wireless sensor network is ideally suited to monitor large structures using nonlinear modulation in a cost-efficient manner. However, existing approaches rely on high sampling rates and resource-demanding computations that are not feasible on low-cost and low-power sensor network devices. We present a new damage indicator that uses the short-time Fourier transform to derive amplitude and phase modulation with less computational effort and memory usage. Evaluation of the proposed method using real experiment data exhibits performance and reliability similar to the conventionally used modulation index. Undersampling is demonstrated, which reduces the memory demand in a test scenario by more than 100 times, and the required energy for sampling and processing more than four times. The loss of accuracy introduced by undersampling is shown to be negligible.

Nonlinear modulation is a promising technique for ultrasonic non-destructive damage identification. A wireless sensor network is ideally suited to monitor large structures using nonlinear modulation in a cost-efficient manner. However, existing approaches rely on high sampling rates and resource-demanding computations that are not feasible on low-cost and low-power sensor network devices. We present a new damage indicator that uses the short-time Fourier transform to derive amplitude and phase modulation with less computational effort and memory usage. Evaluation of the proposed method using real experiment data exhibits performance and reliability similar to the conventionally used modulation index. Undersampling is demonstrated, which reduces the memory demand in a test scenario by more than 100 times, and the required energy for sampling and processing more than four times. The loss of accuracy introduced by undersampling is shown to be negligible.